IEEE VAST CHALLENGE 2022


Entry Name: “RLR-SMU-C3”
VAST Challenge 2022
Challenge 3

Team Members:

Raveena Chakrapani, Singapore Management University, PRIMARY
Leslie Long Nu, Singapore Management University,
Raunak Kapur, Singapore Management University,

Student Team: YES

Tools Used:

Approximately how many hours were spent working on this submission in total? 60

May we post your submission in the Visual Analytics Benchmark Repository after VAST Challenge 2022 is complete? YES

Video

video

Consider the financial status of Engagement’s businesses and residents. Use visual analytics to analyze the available data and develop responses to the questions to be provided. In addition, prepare a video that shows how you used visual analytics to solve this challenge.

Questions

1 – Over the period covered by the dataset, which businesses appear to be more prosperous? Which appear to be struggling? Describe your rationale for your answers. Limit your response to 10 images and 500 words.

The sparkline plot of the businesses’ monthly revenue trend gives us an overview of the prosperity of the businesses in town, namely pubs and restaurant. May 2023’s records are excluded from the data as the records do not include a full month.

The following plot shows that all pubs’ business were at their peaks in the first month of the study, Mar 2022, and faced drastic decline thereafter. Business in Mar 2022 is up to 2x of the average monthly revenue in the duration of the study.

Business Min Max Average Monthly Revenue
Pub 1342 42028.902 97796.03 53127.99 48.8K
Pub 1343 21104.324 59168.76 28886.23 26.7K
Pub 1344 37705.965 89767.68 46226.17 43.2K
Pub 1798 25373.796 56899.34 31047.79 26.7K
Pub 1799 16411.683 38925.96 20509.12 18.8K
Pub 1800 23601.629 52171.44 29038.29 26.3K
Pub 442 13186.967 31726.98 16155.54 14.5K
Pub 443 9966.812 25181.48 12274.15 10.8K
Pub 444 14515.211 28820.72 17108.64 14.8K
Pub 892 19242.812 49720.06 23836.56 21.7K
Pub 893 23315.619 59401.47 30767.57 28.6K
Pub 894 17238.772 42046.89 20991.35 21.0K

As Mar 2022’s revenue is significantly higher than the rest of the months, the following plot is the monthly revenue sparkline plot excluding Mar 2022, which takes a closer look on the trend in the subsequent months.

Rank Business Min Max Average Monthly Revenue
high Pub 1342 42028.902 60783.30 49691.99 48.8K
high Pub 1344 37705.965 52582.48 42876.82 43.2K
high Pub 1798 25373.796 36352.46 29059.20 26.7K
low Pub 442 13186.967 17994.15 14957.74 14.5K
low Pub 443 9966.812 13654.70 11281.28 10.8K
low Pub 444 14515.211 19148.46 16207.71 14.8K
medium Pub 1343 21104.324 33827.26 26556.80 26.7K
medium Pub 1799 16411.683 24175.16 19092.44 18.8K
medium Pub 1800 23601.629 35091.13 27258.82 26.3K
medium Pub 892 19242.812 28047.76 21845.52 21.7K
medium Pub 893 23315.619 33036.13 28564.96 28.6K
medium Pub 894 17238.772 23743.19 19371.69 21.0K

Excluding records in Mar 2022, there are three types of trends for Pubs:

The revenue for struggling and slight recovering pubs by day of the week and by week number is also plotted, to look at the week by week business performance. Generally, pubs are seen to have higher revenue during the weekends, as well as during the new years weekend (2023, week1).

Restaurants

For restaurants, the trend is slightly different. We group restaurant businesses into three groups as well:

Considering their business sizes, the most struggling restaurants are 1347 and 1349, followed by other restaurants with decreasing revenue. Restaurants 897 is most prosperous as it has relatively bigger business size and is still growing, followed by other growing restaurants.

Rank Business Min Max Average Monthly Revenue
high Restaurant 1801 16287.56 20486.18 17989.363 17.1K
high Restaurant 1805 13483.08 15842.06 14817.892 14.7K
high Restaurant 447 12643.98 14111.48 13603.306 13.9K
high Restaurant 449 13439.30 14982.52 14423.340 14.3K
high Restaurant 897 11099.52 13000.32 12178.286 12.7K
low Restaurant 1346 2304.90 2638.35 2497.532 2.4K
low Restaurant 1347 2588.67 3073.77 2820.510 2.7K
low Restaurant 1348 2521.08 2897.55 2751.011 2.9K
low Restaurant 1349 1497.78 1831.68 1632.362 1.5K
low Restaurant 445 2739.80 3023.05 2911.957 3.0K
medium Restaurant 1345 7722.10 8892.40 8376.407 8.7K
medium Restaurant 1802 4963.16 6731.00 5501.640 5.4K
medium Restaurant 1803 3284.25 3932.40 3567.311 3.5K
medium Restaurant 1804 5754.24 6837.60 6304.377 6.8K
medium Restaurant 446 4520.28 5487.72 5050.764 4.8K
medium Restaurant 448 8115.58 11045.98 9120.289 8.8K
medium Restaurant 895 7854.36 12591.84 9143.546 9.0K
medium Restaurant 896 7606.28 8719.68 8224.510 8.0K
medium Restaurant 898 3388.66 3861.30 3648.190 3.5K
medium Restaurant 899 9836.65 13712.55 11044.943 10.7K

While some restaurants show higher revenue/customer traffic during the weekends and some during weekdays, most restaurants see high revenue in New Years Weekend (2023 Week1). It is clear that 1347 and 1349 are the most struggling restaurants, with overall low revenue and some days with nil revenue.

On the other hand, although 1348’s overall revenue is not low, as the business is growthing, it is identified as a prosperous restaurant.

2 – How does the financial health of the residents change over the period covered by the dataset? How do wages compare to the overall cost of living in Engagement? Are there groups that appear to exhibit similar patterns? Describe your rationale for your answers. Limit your response to 10 images and 500 words.

How does the financial health of the residents change over the period covered by the dataset

Are we financially fit?

The dashboard helps us understand the Earning and Expenditure pattern of the participants in the last 15 months. We can notice here that 131 participants have moved from the city in the period as they are not recorded. On scrolling through each and every participant, we see a sharp peak in the Expense category which denotes the rent payment for the shelter in the month of March. This may include the annual maintainance as well along with the rent.

On choosing joviality as one of the filters, we can see those whose cost of living is nearing a straight line over the months are happier than the ones whose cost of living fluctuate

The cost of living may not stay constant when you have kids in the house

How do wages compare to the overall cost of living in Engagement?

Observations:

How much do they spend?

Averaging the proportion in the past 15 months, we can see that participants who spend a lot on education, spend less on other categories which goes on to prove that raising a kid is expensive in the city. Similarly those who spend a lot on shelter, have no such responsibilities and as a result can afford to pay high rent.

As it can be noticed here, the participants tend to spend more on recreation than food. Studying the weekday and weekend patterns, we can see an increase in the expense during the weekend. But overall, even if its a weekday or a weekend, one wants to balance out between work and play and ensures that they do not spend all their time working but spend a considerable amount of time enjoying and refreshing themselves.

Are there groups that appear to exhibit similar patterns?

How similar are the groups